Guillermo Puebla

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it
• Reinforcement Learning — 6 citations into it

Whom Guillermo Puebla trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Ben J. A. Kröse
2. Kaiming He
3. D. Marr
4. Zhong-Qiu Zhao
5. Geoffrey E. Hinton
6. John E. Hummel
7. Ross B. Girshick
8. Volodymyr Mnih
9. Jiwei Li

Papers from Guillermo Puebla's perspective

Ordered by how strongly the researchers Guillermo Puebla trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Human-level control through deep reinforcement learning
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Relation learning in a neurocomputational architecture supports cross-domain transfer (2019) — 6 citations